As new generations of integrated circuit (ICs) employ smaller feature sizes than were contemplated in previous generations, greater demands are placed on the precision of the tools utilized to fabricate these integrated circuits. In particular, minor variation in tool results from run-to-run must be recognized and compensated for by the user.
FIG. 1 shows a schematic diagram of the functioning of a generic semiconductor fabrication system 100. Specifically, fabrication system 100 comprises inputs in the form of operational parameters 102a, 102b, and 102c supplied to fabrication tool 104. Operational parameters 102a-c are settings governing function of fabrication tool 104 for a particular run.
Based upon the input of operational parameters, tool 104 performs a fabrication process upon a semiconductor substrate. The character of this fabrication process is represented by process results 106a and 106b. Process results 106a and 106b may be data measured directly from the changed semiconductor substrate, or may be derived from data measured from the changed semiconductor substrate.
Under ideal conditions, fabrication tool 104 functions on every run to produce the same process result from given operational parameter settings. In reality however, operation of the fabrication tool is subject to a host of complex variables, not all of which can be reliably controlled by the user. Therefore, the performance of the fabrication tool will vary somewhat over time, and the relationship between given operational parameters and process results will drift from run-to-run.
Given the small tolerances of modern semiconductor devices, it is therefore necessary to adjust the operational parameters of the fabrication tool from run-to-run in order to compensate for variation and bring drifting process results back to a desired goal. Conventionally, the user is required to manually determine operating conditions at which the corresponding process results would move back into line with a desired goal. However, the act of generating operating conditions is frequently performed non-systematically by trial and error utilizing operator intuition. Because it lacks a consistent methodology however, correction of process variation by conventional methods is time consuming, error prone, and inconsistent from run-to-run, tool-to-tool, and user-to-user.
Accordingly, new techniques for minimizing run-to-run variation in process results of semiconductor fabrication tools are desirable.
The present invention relates to a method for minimizing run-to-run variation in operation of a semiconductor fabrication tool. In one embodiment, run-to-run variation in process results are minimized by comparing an output from a most recent processing run to a desired fixed goal. A difference between the fixed goal and the output is then calculated. Addition of the difference to the fixed goal creates a mirror image of the output around the fixed goal. The mirror image is used as a target to predict tool behavior for a subsequent processing run in order to bring process results closer to the desired goal.
The method in accordance with the present invention is particularly suited for minimizing variation of a semiconductor fabrication process whose behavior is predicted utilizing a data-based modeling engine. However, the present invention is not limited to controlling this type of fabrication process.
One embodiment of the method in accordance with the present invention comprises the steps of determining a goal of a process result sought to be produced by the tool, and detecting an actual output of the process result from a most recent run of the tool according to an initial recipe. A difference is calculated by subtracting the goal from the actual output, and a mirror image target is calculated by adding the difference to the goal. A suggested recipe is generated from the mirror image target; and a subsequent run of the tool is performed utilizing the suggested recipe to produce a second actual output of the process result that is similar to the goal.
These and other embodiments of the present invention, as well as its advantages and features, are described in more detail in conjunction with the text below and attached figures.